System and method for digital signal processing

ABSTRACT

The present invention provides methods and systems for digitally processing audio signals. Some embodiments receive an audio signal and converting it to a digital signal. The gain of the digital signal may be adjusted a first time, using a digital processing device located between a receiver and a driver circuit. The adjusted signal can be filtered with a first low shelf filter. The systems and methods may compress the filtered signal with a first compressor, process the signal with a graphic equalizer, and compress the processed signal with a second compressor. The gain of the compressed signal can be adjusted a second time. These may be done using the digital processing device. The signal may then be output through an amplifier and driver circuit to drive a personal audio listening device. In some embodiments, the systems and methods described herein may be part of the personal audio listening device.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation patent application ofcurrently-pending U.S. patent application having Ser. No. 12/263,261filed on Oct. 31, 2008, which matures into U.S. Pat. No. 8,284,955 onOct. 9, 2012, and which is a continuation-in-part of U.S. applicationSer. No. 11/947,301, filed on Nov. 29, 2007, now U.S. Pat. No.8,160,274, which claims priority to U.S. Provisional Application No.60/861,711 filed on Nov. 30, 2006, and which is a continuation-in-partof U.S. application Ser. No. 11/703,216, filed on Feb. 7, 2007, whichclaims priority to U.S. Provisional Application No. 60/765,722, filedFeb. 7, 2006. Each of the above applications is incorporated byreference herein in their entirety.

FIELD OF THE INVENTION

The present invention provides for methods and systems for digitallyprocessing an audio signal. Specifically, some embodiments relate todigitally processing an audio signal in a manner such thatstudio-quality sound that can be reproduced using a personal audiolistening device such as a pair of headphones.

BACKGROUND OF THE INVENTION

Historically, studio-quality sound, which can best be described as thefull reproduction of the complete range of audio frequencies that areutilized during the studio recording process, has only been able to beachieved, appropriately, in audio recording studios. Studio-qualitysound is characterized by the level of clarity and brightness which isattained only when the upper-mid frequency ranges are effectivelymanipulated and reproduced. While the technical underpinnings ofstudio-quality sound can be fully appreciated only by experienced recordproducers, the average listener can easily hear the difference thatstudio-quality sound makes.

While various attempts have been made to reproduce studio-quality soundoutside of the recording studio, those attempts have come at tremendousexpense (usually resulting from advanced speaker design, costlyhardware, and increased power amplification) and have achieved onlymixed results. Thus, there exists a need for a process wherebystudio-quality sound can be reproduced outside of the studio withconsistent, high quality, results at a low cost. There exists a furtherneed for audio devices embodying such a process, as well as computerchips embodying such a process that may be embedded within audio devicesor located in a device separate from and not embedded within the audiodevices and, in one embodiment, located as a stand-alone device betweenthe audio device and its speakers. There also exists a need for theability to produce studio-quality sound through inexpensive speakers.

Further, the design of audio systems for vehicles involves theconsideration of many different factors. The audio system designerselects the position and number of speakers in the vehicle. The desiredfrequency response of each speaker must also be determined. For example,the desired frequency response of a speaker that is located on theinstrument panel may be different than the desired frequency response ofa speaker that is located on the lower portion of the rear door panel.

The audio system designer must also consider how equipment variationsimpact the audio system. For example, an audio system in a convertiblemay not sound as good as the same audio system in the same model vehiclethat is a hard top. The audio system options for the vehicle may alsovary significantly. One audio option for the vehicle may include a basic4-speaker system with 40 watts amplification per channel while anotheraudio option may include a 12-speaker system with 200 wattsamplification per channel. The audio system designer must consider allof these configurations when designing the audio system for the vehicle.For these reasons, the design of audio systems is time consuming andcostly. The audio system designers must also have a relatively extensivebackground in signal processing and equalization.

Given those considerations, in order to achieve something approachingstudio-quality sound in a vehicle historically one would have required aconsiderable outlay of money, including expensive upgrades of thefactory-installed speakers. As such, there is a need for a system thatcan reproduce studio-quality sound in a vehicle without having to makesuch expensive outlays.

SUMMARY OF THE INVENTION

The present invention meets the existing needs described above byproviding methods and systems for digitally processing audio signals.Some embodiments receive an audio signal and convert it to a digitalsignal. The gain of the digital signal may be adjusted a first time,using a digital processing device, such as a digital signal processorlocated between a receiver and a driver circuit. The adjusted signal canbe filtered with a first low shelf filter. In various embodiments, thesystems and methods may compress the filtered signal with a firstcompressor, process the signal with a graphic equalizer, and compressthe processed signal with a second compressor. These steps may beperformed using the digital processing device. Some embodiments adjustthe gain of the compressed signal a second time, using the digitalprocessing device and output the signal, from the digital processingdevice through an amplifier and driver circuit in a personal audiolistening device.

In some embodiments, the digital signal represents an audio signal. Theaudio signal can be received wirelessly, e.g. to allow for more freedomof motion for the listener when compared to wired embodiments. Thissignal may be input into a personal audio listening device, such as apair of headphones and these headphones may be coupled to a drivercircuit. Additionally, various embodiments create a sound profile for avehicle where the personal audio listening device will be used.

In various embodiments, the systems and methods described herein filtera signal received from the first low shelf filter with a first highshelf filter prior to compressing the filtered signal with the firstcompressor. The signal can be filtered with a second low shelf filterprior to processing the signal with the graphic equalizer. The signalmay also be filtered with a second high shelf filter after the signal isfiltered with the second low shelf filter.

Some embodiments adjust the gain of the received signal a first timewith a first gain amplifier and adjust the gain of the signal a secondtime with a second gain amplifier. Various cutoff frequencies may beused. For example, the first low shelf filter may have a cutofffrequency at 1000 Hz and the first high shelf filter may have a cutofffrequency at 1000 Hz. In some examples, the graphic equalizer compriseseleven cascading second order filters. Each of the second order filterscan be a bell filter. In some embodiments, the first of the elevenfilters has a center frequency of 30 Hz and the eleventh filter of theeleven filters has a center frequency of 16000 Hz. The second to tenthfilters may be centered at approximately one-octave intervals from eachother. In various embodiments, the second low shelf filter is amagnitude-complementary low-shelf filter.

In some embodiments, an audio system comprises a personal audiolistening device, such as an audio headset. The embodiment might alsoinclude a digital processing device coupled to the headset. The digitalprocessor device may include a first gain amplifier configured toamplify a signal, a first low shelf filter configured to filter theamplified signal and a first compressor configured to compress thefiltered signal. Various embodiments may include a graphic equalizerconfigured to process the filtered signal, a second compressorconfigured to compress the processed signal with a second compressor,and a second gain amplifier configured to amplify the gain of thecompressed signal and to output an output signal. The audio system mayfurther comprise a headset driver coupled to an output of the digitalprocessing device and configured to drive the headset such that it emitssound.

The audio system may also include a first high shelf filter configuredto filter the signal received from the first low shelf filter prior tocompressing the filtered signal with the first compressor. A second lowshelf filter configured to filter a received signal prior to processingthe received signal with the graphic equalizer; and a second high shelffilter configured to filter a received signal after the received signalis filtered with the second low shelf filter may also be included.

Some embodiments include a wireless receiver configured to receive audiosignals wirelessly from a transmitter. In various embodiments, the audiosystem further comprises profile generation circuitry configured toallow a user to create a sound profile for an area by listening to musicin the area and adjusting the audio system. A second low shelf filterthat is a magnitude-complementary low-shelf filter may also be used tofilter the audio signal.

In some embodiments of the methods and systems described herein processan audio signal. This can be done by receiving an audio signal,adjusting a gain of the audio signal a first time using a separatedigital processing device located between a radio head unit and aspeaker, and processing the audio signal with a first low shelf filterusing the digital processing device. Various embodiments process theaudio signal with a first high shelf filter using the digital processingdevice, process the audio signal with a first compressor using thedigital processing device, and process the audio signal with a secondlow shelf filter using the digital processing device. These embodimentsmay also process the audio signal with a second high shelf filter usingthe digital processing device, process the audio signal with a graphicequalizer using the digital processing device, process the audio signalwith a second compressor using the digital processing device.Additionally, these embodiments may adjust the gain of the audio signala second time using the digital processing device and output the audiosignal from the digital processing device to a headset driver. Variousembodiments may connect the driver to a set of headphones, profile for avehicle where the headphones will be used and receive the audio signalwirelessly.

Other features and aspects of the invention will become apparent fromthe following detailed description, taken in conjunction with theaccompanying drawings, which illustrate, by way of example, the featuresin accordance with embodiments of the invention. The summary is notintended to limit the scope of the invention, which is defined solely bythe claims attached hereto.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention, in accordance with one or more variousembodiments, is described in detail with reference to the followingfigures. The drawings are provided for purposes of illustration only andmerely depict typical or example embodiments of the invention. Thesedrawings are provided to facilitate the reader's understanding of theinvention and shall not be considered limiting of the breadth, scope, orapplicability of the invention. It should be noted that for clarity andease of illustration these drawings are not necessarily made to scale.

FIG. 1 illustrates a block diagram of one embodiment of the digitalsignal processing method of the present invention.

FIG. 2 illustrates the effect of a low-shelf filter used in oneembodiment of the digital signal processing method of the presentinvention.

FIG. 3 illustrates how a low-shelf filter can be created using high-passand low-pass filters.

FIG. 4 illustrates the effect of a high-shelf filter used in oneembodiment of the digital signal processing method of the presentinvention.

FIG. 5 illustrates the frequency response of a bell filter used in oneembodiment of the digital signal processing method of the presentinvention.

FIG. 6 illustrates a block diagram of one embodiment of a graphicequalizer used in one embodiment of the digital signal processing methodof the present invention.

FIG. 7 illustrates a block diagram showing how a filter can beconstructed using the Mitra-Regalia realization.

FIG. 8 illustrates the effect of magnitude-complementary low-shelffilters that may be used in one embodiment of the digital signalprocessing method of the present invention.

FIG. 9 illustrates a block diagram of an implementation of amagnitude-complementary low-shelf filter that may be used in oneembodiment of the digital signal processing method of the presentinvention.

FIG. 10 illustrates the static transfer characteristic (the relationshipbetween output and input levels) of a compressor used in one embodimentof the digital signal processing method of the present invention.

FIG. 11 illustrates a block diagram of a direct form type 1implementation of second order transfer function used in one embodimentof the digital signal processing method of the present invention.

FIG. 12 illustrates a block diagram of a direct form type 1implementation of second order transfer function used in one embodimentof the digital signal processing method of the present invention.

FIG. 13 illustrates a block diagram in accordance with one embodiment ofthe present invention.

The figures are not intended to be exhaustive or to limit the inventionto the precise form disclosed. It should be understood that theinvention can be practiced with modification and alteration, and thatthe invention be limited only by the claims and the equivalents thereof.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

It is to be understood that the present invention is not limited to theparticular methodology, compounds, materials, manufacturing techniques,uses, and applications described herein, as these may vary. It is alsoto be understood that the terminology used herein is used for thepurpose of describing particular embodiments only, and is not intendedto limit the scope of the present invention. It must be noted that asused herein and in the appended embodiments, the singular forms “a,”“an,” and “the” include the plural reference unless the context clearlydictates otherwise. Thus, for example, a reference to “an audio device”or separate device is a reference to one or more audio devices orseparate devices that implement the systems and methods of the presentinvention, whether integrated or not and includes equivalents thereofknown to those skilled in the art. Similarly, for another example, areference to “a step” or “a means” is a reference to one or more stepsor means and may include sub-steps and subservient means. Allconjunctions used are to be understood in the most inclusive sensepossible. Thus, the word “or” should be understood as having thedefinition of a logical “or” rather than that of a logical “exclusiveor” unless the context clearly necessitates otherwise. Language that maybe construed to express approximation should be so understood unless thecontext clearly dictates otherwise.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meanings as commonly understood by one of ordinary skillin the art to which this invention belongs. Preferred methods,techniques, devices, and materials are described, although any methods,techniques, devices, or materials similar or equivalent to thosedescribed herein may be used in the practice or testing of the presentinvention. Structures described herein are to be understood also torefer to functional equivalents of such structures.

1.0 Overview

First, some background on linear time-invarient systems is helpful. Alinear, time-invariant (LTI) discrete-time filter of order N with inputx[k] and output y[k] is described by the following difference equation:

y[k]=b ₀ x[k]+b ₁ x[k−1]+ . . . +b _(N) x[k−N]+a ₁ y[k−1]+a ₂ y[k−2]+ .. . +a _(N) y[k−N]

where the coefficients {b0, b1, . . . , bN, a1, a2, . . . aN} are chosenso that the filter has the desired characteristics (where the termdesired can refer to time-domain behavior or frequency domain behavior).

The difference equation above can be excited by an impulse function,δ[k], whose value is given by

${\delta \lbrack k\rbrack} = \{ \begin{matrix}{1,} & {k = 0} \\{0,} & {k \neq 0}\end{matrix} $

When the signal δ[k] is applied to the system described by the abovedifference equation, the result is known as the impulse response, h[k].It is a well-known result from system theory that the impulse responseh[k] alone completely characterizes the behavior of a LTI discrete-timesystem for any input signal. That is, if h[k] is known, the output y[k]for an input signal x[k] can be obtained by an operation known asconvolution. Formally, given h[k] and x[k], the response y[k] can becomputed as

${y\lbrack k\rbrack} = {\sum\limits_{n = 0}^{\infty}{{h\lbrack n\rbrack}{x\lbrack {k - n} \rbrack}}}$

Some background on the z-transform is also helpful. The relationshipbetween the time-domain and the frequency-domain is given by a formulaknown as the z-transform. The z-transform of a system described by theimpulse response h[k] can be defined as the function H(z) where

${H(z)} = {\sum\limits_{k = 0}^{\infty}{{h\lbrack k\rbrack}z^{- k}}}$

and z is a complex variable with both real and imaginary parts. If thecomplex variable is restricted to the unit circle in the complex plane(i.e., the region described by the relationship [z|=1), what results isa complex variable that can be described in radial form as

z=ε ^(jθ),where 0≦θ≦2π and j=√{square root over (−1)}

Some background on the discrete-time Fourier transform is alsoinstructive. With z described in radial form, the restriction of thez-transform to the unit circle is known as the discrete-time Fouriertransform (DTFT) and is given by

${H( \varepsilon^{j\theta} )} = {\sum\limits_{k = 0}^{\infty}{{h\lbrack k\rbrack}^{{- j}\; k\; \theta}}}$

Of particular interest is how the system behaves when it is excited by asinusoid of a given frequency. One of the most significant results fromthe theory of LTI systems is that sinusoids are Eigen functions of suchsystems. This means that the steady-state response of an LTI system to asinusoid sin(θ0k) is also a sinusoid of the same frequency θ0, differingfrom the input only in amplitude and phase. In fact, the steady-stateoutput, yss[k] of the LTI system when driven by and input x[k]=sin(θ0k)is given by y_(δδ[k]=A) sin(θ₀k+φ₀)

where

A=|H(ε^(jθ) ₀)

and

φ₀=arg(H(e ^(jθ) ₀)

Finally, some background on frequency response is needed. The equationsabove are significant because they indicate that the steady-stateresponse of an LTI system when driven by a sinusoid is a sinusoid of thesame frequency, scaled by the magnitude of the DTFT at that frequencyand offset in time by the phase of the DTFT at that frequency. For thepurposes of the present invention, what is of concern is the amplitudeof the steady state response, and that the DTFT provides us with therelative magnitude of output-to-input when the LTI system is driven by asinusoid. Because it is well-known that any input signal may beexpressed as a linear combination of sinusoids (the Fourierdecomposition theorem), the DTFT can give the response for arbitraryinput signals. Qualitatively, the DTFT shows how the system responds toa range of input frequencies, with the plot of the magnitude of the DTFTgiving a meaningful measure of how much signal of a given frequency willappear at the system's output. For this reason, the DTFT is commonlyknown as the system's frequency response.

2.0 Digital Signal Processing

FIG. 1 illustrates an example digital signal process flow of a method100 according to one embodiment of the present invention. Referring nowto FIG. 1, method 100 includes the following steps: input gainadjustment 101, first low shelf filter 102, first high shelf filter 103,first compressor 104, second low shelf filter 105, second high shelffilter 106, graphic equalizer 107, second compressor 108, and outputgain adjustment 109.

In one embodiment, digital signal processing method 100 may take asinput audio signal 110, perform steps 101-109, and provide output audiosignal 111 as output. In one embodiment, digital signal processingmethod 100 is executable on a computer chip, such as, withoutlimitation, a digital signal processor, or DSP. In one embodiment, sucha chip may be one part of a larger audio device, such as, withoutlimitation, a radio, MP3 player, game station, cell phone, television,computer, or public address system. In one such embodiment, digitalsignal processing method 100 may be performed on the audio signal beforeit is outputted from the audio device. In one such embodiment, digitalsignal processing method 100 may be performed on the audio signal afterit has passed through the source selector, but before it passes throughthe volume control.

In one embodiment, steps 101-109 may be completed in numerical order,though they may be completed in any other order. In one embodiment,steps 101-109 may exclusively be performed, though in other embodiments,other steps may be performed as well. In one embodiment, each of steps101-109 may be performed, though in other embodiments, one or more ofthe steps may be skipped.

In one embodiment, input gain adjustment 101 provides a desired amountof gain in order to bring input audio signal 110 to a level that willprevent digital overflow at subsequent internal points in digital signalprocessing method 100.

In one embodiment, each of the low-shelf filters 102, 105 is a filterthat has a nominal gain of 0 dB for all frequencies above a certainfrequency termed the corner frequency. For frequencies below the cornerfrequency, the low-shelving filter has a gain of ±G dB, depending onwhether the low-shelving filter is in boost or cut mode, respectively.This is shown in FIG. 2.

In one embodiment, the systems and methods described herein may beimplemented in a separate device that is located (e.g., wired orwirelessly) between, for example, a vehicle head unit, radio or otheraudio source and the vehicle's or other audio source's speaker system.This device may be installed at the factory. In another embodiment,however, this device may be retrofitted into a preexisting vehicle orother audio system. The device might also be used in conjunction withother audio or video equipment and speaker systems in addition tovehicle audio systems. For example, the device might be used inconjunction with a home stereo system and home stereo speakers or avehicle DVD video/audio system and it may be wired or wireless.

FIG. 2 illustrates the effect of a low-shelf filter being implemented byone embodiment of the present invention. Referring now to FIG. 2, thepurpose of a low-shelving filter is to leave all of the frequenciesabove the corner frequency unaltered, while boosting or cutting allfrequencies below the corner frequency by a fixed amount, G dB. Also,note that the 0 dB point is slightly higher than the desired 1000 Hz. Itis standard to specify a low-shelving filter in cut mode to have aresponse that is at −3 dB at the corner frequency, whereas alow-shelving filter in boost mode is specified such that the response atthe corner frequency is at G−3 dB—namely, 3 dB down from maximum boost.Indeed, all of the textbook formulae for creating shelving filters leadto such responses. This leads to a certain amount of asymmetry, wherefor almost all values of boost or cut G, the cut and boost low-shelvingfilters are not the mirror images of one another. This is something thatneeded to be address by the present invention, and required aninnovative approach to the filters' implementations.

Ignoring for now the asymmetry, the standard method for creating alow-shelving filter is as the weighted sum of high-pass and low-passfilters. For example, let's consider the case of a low-shelving filterin cut mode with a gain of −G dB and a corner frequency of 1000 Hz. FIG.3 shows a high-pass filter with a 1000 cutoff frequency and a low-passfilter with a cutoff frequency of 1000 Hz, scaled by −G dB. Theaggregate effect of these two filters applied in series looks like thelow-shelving filter in FIG. 2. In practice, there are some limitationson the steepness of the transition from no boost or cut to G dB of boostor cut. FIG. 3 illustrates this limitation, with the corner frequencyshown at 1000 Hz and the desired G dB of boost or cut not being achieveduntil a particular frequency below 1000 Hz. It should be noted that allof the shelving filters in the present invention are first-ordershelving filters, which means they can usually be represented by afirst-order rational transfer function:

${H(z)} = \frac{b_{0} + {b_{1}z^{- 1}}}{1 + {a_{1}z^{- 1}}}$

In some embodiments, each of the high-shelf filters 103, 106 is nothingmore than the mirror image of a low-shelving filter. That is, allfrequencies below the corner frequency are left unmodified, whereas thefrequencies above the corner frequency are boosted or cut by G dB. Thesame caveats regarding steepness and asymmetry apply to thehigh-shelving filter. FIG. 4 illustrates the effect of a high-shelffilter implemented by an embodiment of the present invention. Referringnow to FIG. 4, a 1000 Hz high-shelving filter is shown.

FIG. 5 illustrates an example frequency response of a bell filterimplemented by method 100 according to one embodiment of the presentinvention. As shown in FIG. 5, each of the second order filters achievesa bell-shaped boost or cut at a fixed center frequency, with F1(z)centered at 30 Hz, F11(z) centered at 16000 Hz, and the other filters inbetween centered at roughly one-octave intervals. Referring to FIG. 5, abell-shaped filter is shown centered at 1000 Hz. The filter has anominal gain of 0 dB for frequencies above and below the centerfrequency, 1000 Hz, a gain of −G dB at 1000 Hz, and a bell-shapedresponse in the region around 1000 Hz.

The shape of the filter is characterized by a single parameter: thequality factor, Q. The quality factor is defined as the ratio of thefilter's center frequency to its 3-dB bandwidth, B, where the 3-dBbandwidth is illustrated as in the figure: the difference in Hz betweenthe two frequencies at which the filter's response crosses the −3 dBpoint.

FIG. 6 illustrates an example graphic equalizer block 600 according toone embodiment of the present invention. Referring now to FIG. 6,graphic equalizer 600 consists of a cascaded bank of eleven second-orderfilters, F₁(z),F₂(z), . . . ,F₁₁(z). In one embodiment, graphicequalizer 107 (as shown in FIG. 1) is implemented as graphic equalizer600.

One embodiment may have eleven second-order filters. In this embodimenteach of eleven second-order filters might be computed from formulas thatresemble this one:

${F(z)} = \frac{b_{0} + {b_{1}z^{- 1}} + {b_{2}z^{- 2}}}{1 + {a_{1}z^{- 1}} + {a_{2}z^{- 2}}}$

Using such an equation results in one problem: each of the fivecoefficients above, {b₀,b₁,b₂,a₁,a₂} depends directly on the qualityfactor, Q, and the gain, G. This means that for the filter to betunable, that is, to have variable Q and G, all five coefficients mustbe recomputed in real-time. This can be problematic, as suchcalculations could easily consume the memory available to performgraphic equalizer 107 and create problems of excessive delay or fault,which is unacceptable. This problem can be avoided by utilizing theMitra-Regalia Realization.

A very important result from the theory of digital signal processing(DSP) is used to implement the filters used in digital signal processingmethod 100. This result states that a wide variety of filters(particularly the ones used in digital signal processing method 100) canbe decomposed as the weighted sum of an allpass filter and a feedforward branch from the input. The importance of this result will becomeclear. For the time being, suppose that a second-order transferfunction, H(z), is being implemented to describes a bell filter centeredat fc with quality factor Q and sampling frequency Fs by

${H(z)} = \frac{b_{0} + {b_{1}z^{- 1}} + {b_{2}z^{- 2}}}{1 + {a_{1}z^{- 1}} + {a_{2}z^{- 2}}}$

Ancillary quantities k1, k2 can be defined by

$k_{1} = \frac{1 - {\tan ( \frac{\pi \; f_{c}}{{QF}_{s}} )}}{1 + {\tan ( \frac{\pi \; f_{c}}{{QF}_{s}} )}}$$k_{2} = {- {\cos ( \frac{2\pi \; f_{c}}{F_{s}} )}}$

and transfer function, A(z) can be defined by

${A(z)} = \frac{k_{2} + {{k_{1}( {1 + k_{2}} )}z^{- 1}} + z^{- 2}}{1 + {{k_{1}( {1 + k_{2}} )}z^{- 1}} + {k_{2}z^{- 2}}}$

A(z) can be verified to be an allpass filter. This means that theamplitude of A(z) is constant for all frequencies, with only the phasechanging as a function of frequency. A(z) can be used as a buildingblock for each bell-shaped filter. The following very important resultcan be shown:

${H(z)} = {{\frac{1}{2}( {1 + G} ){A(z)}} + {\frac{1}{2}( {1 - G} )}}$

This is the crux of the Mitra-Regalia realization. A bell filter withtunable gain can be implemented to show the inclusion of the gain G in avery explicit way. This is illustrated in FIG. 7, which illustrates anexample filter constructed using the Mitra-Regalia realization accordingto one embodiment of the present invention.

There is a very good reason for decomposing the filter in such anon-intuitive manner. Referring to the above equation, every one of thea and b coefficients needs to be re-computed whenever G gets changed(i.e., whenever one of the graphic EQ “slider” is moved). Although thecalculations that need to be performed for the a and b coefficients havenot been shown, they are very complex and time-consuming and it simplyis not practical to recompute them in real time. However, in a typicalgraphic EQ, the gain G and quality factor Q remain constant and only Gis allowed to vary. A(z) does not depend in any way on the gain, G andthat if Q and the center-frequency fc remain fixed (as they do in agraphic EQ filter), then k1 and k2 remain fixed regardless of G. Thus,these variables only need to be computed once. Computing the gainvariable is accomplished by varying a couple of simple quantities inreal time:

$\frac{1}{2}( {1 + G} )$ and$\frac{1}{2}( {1 - G} )$

These are very simple computations and only require a couple of CPUcycles. This leaves only the question of how to implement the allpasstransfer function, A(z). The entire graphic equalizer bank thus consistsof 11 cascaded bell filters, each of which is implemented via its ownMitra-Regalia realization:

$\begin{matrix} {F_{1}(z)}arrow  & {{{fixed}k}_{1}^{1},k_{2}^{1},{{variable}\mspace{14mu} G_{1}}} \\ {F_{2}(z)}arrow  & {{{fixed}k}_{1}^{2},k_{2}^{2},{{variable}\mspace{14mu} G_{2}}} \\\vdots & \vdots \\ {F_{11}(z)}arrow  & {{{fixed}k}_{1}^{11},k_{2}^{11},{{variable}\mspace{14mu} G_{11}}}\end{matrix}$

It can be seen from that equation that the entire graphic equalizer bankdepends on a total of 22 fixed coefficients that need to be calculatedonly once and stored in memory. The “tuning” of the graphic equalizer isaccomplished by adjusting the parameters G1, G2, . . . , G11. See FIG. 6to see this in schematic form. The Mitra-Regalia realization may be usedover and over in the implementation of the various filters used digitalsignal processing method 100. Mitra-Regalia may also be useful inimplementing the shelving filters, where it is even simpler because theshelving filters use first-order filter. The net result is that ashelving filter is characterized by a single allpass parameter, k, and again, G. As with the bell filters, the shelving filters are at fixedcorner frequencies (in fact, all of them have 1 kHz as their cornerfrequency) and the bandwidth is also fixed. All told, four shelvingfilters are completely described simply by

H ₁(z)→fixed k ¹,variable G ₁

H ₂(z)→fixed k ²,variable G ₂

H ₃(z)→fixed k ³,variable G ₃

H ₄(z)→fixed k ⁴,variable G ₄

As discussed above, there is an asymmetry in the response of aconventional shelving filter when the filter is boosting versus when itis cutting. This is due, as discussed, to the design technique havingdifferent definitions for the 3-dB point when boosting than whencutting. Digital signal processing method 100 relies on the filtersH1(z) and H3(z) being the mirror images of one another and the sameholds for H2(z) and H4(z). This led to the use of a special filterstructure for the boosting shelving filters, one that leads to perfectmagnitude cancellation for H1,H3 and H2,H4, as shown in FIG. 8. Thistype of frequency response is known as magnitude complementary. Thisstructure is unique to the present invention. In general, it is a simplemathematical exercise to derive for any filter H(z) a filter withcomplementary magnitude response. The filter H−1(z) works, but may notbe stable or implementable function of z, in which case the solution ismerely a mathematical curiosity and is useless in practice. This is thecase with a conventional shelving filter. The equations above show howto make a bell filter from an allpass filter. These equation appliesequally well to constructing a shelving filter beginning with afirst-order allpass filter, A(z), where

${A(z)} = \frac{\alpha - z^{- 1}}{1 - {\alpha \; z^{- 1}}}$

and α is chosen such that

$\alpha = \frac{( {1 - {\sin ( \frac{2\pi \; f_{c}}{F_{s}} )}} )}{\cos ( \frac{2\pi \; f_{c}}{F_{s}} )}$

where fc is the desired corner frequency and Fs is the samplingfrequency. Applying the above equations and re-arranging terms, this canbe expressed as

${H(z)} = {\frac{1 + G}{2}\{ {1 + {\frac{1 - G}{1 + G}{A(z)}}} \}}$

This is the equation for a low-shelving filter. (A high-shelving filtercan be obtained by changing the term (1−G) to (G−1)). Taking the inverseof H(z) results in the following:

$\frac{1}{H(z)} = \frac{2}{( {1 + G} )( {1 + {\frac{1 - G}{1 + G}{A(z)}}} )}$

This equation is problematic because it contains a delay-free loop,which means that it cannot be implemented via conventionalstate-variable methods. Fortunately, there are some recent results fromsystem theory that show how to implement rational functions withdelay-free loops. Fontana and Karjalainen (IEEE Signal ProcessingLetters, Vol. 10, No. 4, April 2003) show that each step can be “split”in time into two “sub-steps.”

FIG. 9 illustrates an example magnitude-complementary low-shelf filteraccording to one embodiment of the present invention. During the firstsub-step (labeled “subsample 1”), feed filter A(z) with zero input andcompute its output, 10[k]. During this same subsample, calculate theoutput y[k] using the value of 10[k], which from the equationimmediately above can be performed as follows:

$\begin{matrix}{{y\lbrack k\rbrack} = {\frac{1}{1 + {\alpha \frac{1 - G}{1 + G}}}\{ {{\frac{2}{1 + G}{x\lbrack k\rbrack}} + ( {\frac{1 - G}{1 + G}{l_{0}\lbrack k\rbrack}} \}} }} \\{= {\frac{2}{( {1 + G} ) + {\alpha ( {1 - G} )}}\{ {{x\lbrack k\rbrack} + {\frac{1 - G}{2}{l_{0}\lbrack k\rbrack}}} \}}}\end{matrix}$

It can be seen from FIG. 9 that these two calculations correspond to thecase where the switches are in the “subsample 1” position. Next, theswitches are thrown to the “subsample 2” position and the only thingleft to do is update the internal state of the filter A(z). Thisunconventional filter structure results in perfect magnitudecomplementarity, 11. This can be exploited for the present invention inthe following manner: when the shelving filters of digital signalprocessing method 100 are in “cut” mode, the following equation can beused:

${H(z)} = {\frac{1 + G}{2}\{ {1 + {\frac{1 - G}{1 + G}{A(z)}}} \}}$

However, when the shelving filters of digital signal processing method100 are in “boost” mode, the following equation can be used with thesame value of G as used in “cut” mode:

$\begin{matrix}{{y\lbrack k\rbrack} = {\frac{1}{1 + {\alpha \frac{1 - G}{1 + G}}}\{ {{\frac{2}{1 + G}{x\lbrack k\rbrack}} + {\frac{1 - G}{1 + G}{l_{0}\lbrack k\rbrack}}} \}}} \\{= {\frac{2}{( {1 + G} ) + {\alpha ( {1 - G} )}}\{ {{x\lbrack k\rbrack} + {\frac{1 - G}{2}{l_{0}\lbrack k\rbrack}}} \}}}\end{matrix}$

This results in shelving filters that are perfect mirror images of oneanother, as illustrated in FIG. 8, which is what is needed for digitalsignal processing method 100. (Note: Equation 16 can be changed to makea high-shelving filter by changing the sign on the (1−G)/2 term). FIG. 8illustrates the effect of a magnitude-complementary low-shelf filterimplemented by an embodiment of the present invention.

Each of the compressors 104, 108 is a dynamic range compressor designedto alter the dynamic range of a signal by reducing the ratio between thesignal's peak level and its average level. A compressor is characterizedby four quantities: the attack time, Tatt, the release time, Trel, thethreshold, KT, and the ratio, r. In brief, the envelope of the signal istracked by an algorithm that gives a rough “outline” of the signal'slevel. Once that level surpasses the threshold, KT, for a period of timeequal to Tatt, the compressor decreases the level of the signal by theratio r dB for every dB above KT. Once the envelope of the signal fallsbelow KT for a period equal to the release time, Trel, the compressorstops decreasing the level. FIG. 10 illustrates a static transfercharacteristic (relationship between output and input levels) of acompressor implemented in accordance with one embodiment of the presentinvention.

It is instructive to examine closely the static transfer characteristic.Assume that the signal's level, L[k] at instant k has been somehowcomputed. For instructive purposes, a one single static level, L, willbe considered. If L is below the compressor's trigger threshold, KT, thecompressor does nothing and allows the signal through unchanged. If,however, L is greater than KT, the compressor attenuates the inputsignal by r dB for every dB by which the level L exceeds KT.

It is instructive to consider an instance where L is greater than KT,which means that 20 log₁₀(L)>20 log₁₀(KT). In such an instance, theexcess gain, i.e., the amount in dB by which the level exceeds thethreshold, is: g_(excess)=20 log₁₀(L)−20 log₁₀(KT). As the compressorattenuates the input by r dB for every dB of excess gain, the gainreduction, gR, can be expressed as

${gR} = {\frac{g_{excess}}{R} = {\frac{1}{R} \cdot ( {{20{\log_{10}(L)}} - {20{\log_{10}({KT})}}} )}}$

From that, it follows that that with the output of the compressor, ygiven by 20 log₁₀(y)=gR*20 log₁₀(x), that the desired output-to-inputrelationship is satisfied.

Conversion of this equation to the linear, as opposed to thelogarithmic, domain yields the following:

$y = {( 10^{\log_{10}{(x)}} )\frac{1}{R}( {{\log_{10}(L)} - {\log_{10}({KT})}} )}$

The most important part of the compressor algorithm is determining ameaningful estimate of the signal's level. This is accomplished in afairly straightforward way: a running “integration” of the signal'sabsolute value is kept, where the rate at which the level is integratedis determined by the desired attack time. When the instantaneous levelof the signal drops below the present integrated level, the integratedlevel is allowed to drop at a rate determined by the release time. Givenattack and release times Tatt and Trel, the equation used to keep trackof the level, L[k] is given by

${L\lbrack k\rbrack} = \{ {{\begin{matrix}{( {1 - \alpha_{att}} ){{x\lbrack k\rbrack} + {\alpha_{att}{L\lbrack {k - 1} \rbrack}}}} & {{{for}\mspace{14mu} {{x\lbrack k\rbrack}}} \geq {L\lbrack {k - 1} \rbrack}} \\{( {1 - \alpha_{rel}} ){{x\lbrack k\rbrack} + {\alpha_{rel}{L\lbrack {k - 1} \rbrack}}}} & {{{for}\mspace{14mu} {{x\lbrack k\rbrack}}} < {L\lbrack {k - 1} \rbrack}}\end{matrix}{where}\alpha_{att}} = {{{\exp ( \frac{1}{F_{g}T_{att}} )}{and}\alpha_{rel}} = {\exp ( \frac{1}{5F_{g}T_{rel}} )}}} $

At every point of the level calculation as described above, L[k] ascomputed is compared to the threshold KT, and if L[k] is greater thanKT, the input signal, x[k], is scaled by an amount that is proportionalto the amount by which the level exceeds the threshold. The constant ofproportionality is equal to the compressor ratio, r. After a great dealof mathematical manipulation, the following relationship between theinput and the output of the compressor is established:

With the level L[k] as computed using, for example, the equation forL[k], above, the quantity Gexcess by is computed as

G _(excess) =L[k]K _(T) ⁻¹

which represents the amount of excess gain. If the excess gain is lessthan one, the input signal is not changed and passed through to theoutput. In the event that the excess gain exceeds one, the gainreduction, GR is computed by:

$G_{R} = {{( G_{excess} )\frac{1 - r}{r}} = ( {{L\lbrack k\rbrack}K_{T}^{- 1}} )^{\frac{1 - r}{r}}}$

and then the input signal is scaled by GR and sent to the output:

output[k]=G _(R) x[k]

Through this procedure, an output signal whose level increases by 1/r dBfor every 1 dB increase in the input signal's level is created.

In practice, computing the inverse K_(T) ⁻¹ for the above equations canbe time consuming, as certain computer chips are very bad at division inreal-time. As KT is known in advance and it only changes when the userchanges it, a pre-computed table of K_(T) ⁻¹ values can be stored inmemory and used as needed. Similarly, the exponentiation operation inthe above equation calculating GR is extremely difficult to perform inreal time, so pre-computed values can be used as an approximation. Sincequantity GR is only of concern when Gexcess is greater than unity, alist of, say, 100 values of GR, pre-computed at integer values of GRfrom GR=1 to GR=100 can be created for every possible value of ratio r.For non-integer values of GR (almost all of them), the quantity in theabove equation calculating GR can be approximated in the following way.Let interp be the amount by which Gexcess exceeds the nearest integralvalue of Gexcess. In other words,

interp=G _(excess)−┐(G _(excess))┘

and let GR,0 and GR,1 refer to the pre-computed values

$G_{R,0} = \lfloor ( G_{excess} ) \rfloor^{\frac{1 - r}{r}}$and$G_{R,1} = \lfloor ( {1 + G_{excess}} ) \rfloor^{\frac{1 - r}{r}}$

Linear interpolation may then be used to compute an approximation of GRas follows:

G _(R) =G _(R,0)interp*(G _(R,1) −G _(R,0))

The error between the true value of GR and the approximation in theabove equation can be shown to be insignificant for the purposes of thepresent invention. Furthermore, the computation of the approximate valueof GR requires only a few arithmetic cycles and several reads frompre-computed tables. In one embodiment, tables for six different valuesof ratio, r, and for 100 integral points of Gexcess may be stored inmemory. In such an embodiment, the entire memory usage is only 600 wordsof memory, which can be much more palatable than the many hundred cyclesof computation that would be necessary to calculate the true value of GRdirectly. This is a major advantage of the present invention.

Each of the digital filters in digital signal processing method 100 maybe implemented using any one of a variety of potential architectures orrealizations, each of which has its trade-offs in terms of complexity,speed of throughput, coefficient sensitivity, stability, fixed-pointbehavior, and other numerical considerations. In a specific embodiment,a simple architecture known as a direct-form architecture of type 1(DF1) may be used. The DF1 architecture has a number of desirableproperties, not the least of which is its clear correspondence to thedifference equation and the transfer function of the filter in question.All of the digital filters in digital signal processing method 100 areof either first or second order.

The second-order filter will be examined in detail first. As discussedabove, the transfer function implemented in the second-order filter isgiven by

${H(z)} = \frac{b_{0} + {b_{1}z^{- 1}} + {b_{2}z^{- 2}}}{1 + {a_{1}z^{- 1}} + {a_{2}z^{- 2}}}$

which corresponds to the difference equation

y[k]=b ₀ x[k]+b ₁ x[k−1]+b ₂ x[k−2]−a ₁ y[k−1]−a ₂ y[k−2]

FIG. 11 illustrates the DF1 architecture for a second-order filteraccording to one embodiment of the present invention. As shown in FIG.11, the multiplier coefficients in this filter structure correspond tothe coefficients in the transfer function and in the difference equationabove. The blocks marked with the symbol z−1 are delay registers, theoutputs of which are required at every step of the computation. Theoutputs of these registers are termed state variables and memory isallocated for them in some embodiments of digital signal processingmethod 100. The output of the digital filter is computed as follows:

Initially, each of the state variables is set to zero. In other words,

x[−1]=x[−2]=y[−1]=y[−2]=0.

At time k=0 the following computation is done, according to FIG. 11:

y[0]=b ₀ x[0]+b ₁ x[−1]+b ₂ x[−2]−a ₁ y[−1]−a ₂ y[−2].

Then, the registers are then updated so that the register marked byx[k−1] now holds x[0], the register marked by x[k−2] now holds x[−1],the register marked by y[k−1] holds y[0], and the register marked byy[k−2] holds y[−1].

At time k=1 the following computation is done:

y[1]=b ₀ x[1]+b ₁ x[0]+b ₂ x[−1]−a ₁ y[0]−a ₂ y[−1].

Then, the register update is again completed so that the register markedby x[k−1] now holds x[1], the register marked by x[k−2] now holds x[0],the register marked by y[k−1] holds y[1], and the register marked byy[k−2] holds y[0].

This process is then repeated over and over for all instants k: A newinput, x[k], is brought in, a new output y[k] is computed, and the statevariables are updated.

In general, then, the digital filtering operation can be viewed as a setof multiplications and additions performed on a data stream x[0], x[1],x[2], . . . using the coefficients b0, b1, b2, a1, a2 and the statevariables x[k−1], x[k−2], y[k−1], y[k−2].

The manifestation of this in specific situations is instructive.Examination of the bell filter that constitutes the fundamentalbuilding-block of graphic equalizer 107 is helpful. As discussed above,the bell filter is implemented with a sampling frequency Fs, gain G at acenter frequency fc, and quality factor Q as

${H(z)} = {{\frac{1}{2}( {1 + G} ){A(z)}} + {\frac{1}{2}( {1 - G} )}}$

where A(z) is an allpass filter defined by

${A(z)} = \frac{k_{2} + {{k_{1}( {1 + k_{2}} )}z^{- 1}} + z^{- 2}}{1 + {{k_{1}( {1 + k_{2}} )}z^{- 1}} + {k_{2}z^{- 2}}}$

where k1 and k2 are computed from fc and Q via the equations

$k_{1} = \frac{1 - {\tan ( \frac{\pi \; f_{c}}{{QF}_{s}} )}}{1 + {\tan ( \frac{\pi \; f_{c}}{{QF}_{s}} )}}$and $k_{2} = {- {\cos ( \frac{2\pi \; f_{c}}{F_{s}} )}}$

The values k1 and k2 are pre-computed and stored in a table in memory.To implement a filter for specific values of Q and fc, the correspondingvalues of k1 and k2 are looked up in this table. Since there are elevenspecific values of fc and sixteen specific values of Q in the algorithm,and the filter operates at a single sampling frequency, Fs, and only k2depends on both fc and Q, the overall storage requirements for the k1and k2 coefficient set is quite small (11.times.16.times.2 words atworst).

Observe from the equation above for A(z) that its coefficients aresymmetric. That is, the equations can be re-written as

${A(z)} = \frac{z^{- 2} + {geq\_ b1z}^{- 1} + {geq\_ b0}}{1 + {geq\_ b1z}^{- 1} + {geq\_ b0z}^{- 2}}$where geq_(b 0) = k₂ and geq_(b 1) = k₁(1 + k₂)

Observe that A(z) as given in the above equation implies the differenceequation

y[k]=geq _(b0)(x[k]+geq _(b1) x[k−1]+x[k−2]−geq _(b1) y[k−1]−geq _(b0)y[k−2]

which can be rearranged to yield

y[k]=geq _(b0)(x[k]−y[k−2])+geq _(b1)(x[k−1]−y[k−1])+x[k−2]

In a specific embodiment, the state variables may be stored in arraysxv[ ] and yv[ ] with xv[0] corresponding to x[k−2], xv[1] correspondingto x[k−1], yv[0] corresponding to y[k−2] and yv[1] corresponding toy[k−1]. Then the following code-snippet implements a single step of theallpass filter:

void allpass(float *xv, float *yv, float *input, float *output) {*output = geq_b0 * (*input − yv[0]) + geq_b1 * (xv[1] − yv[1]) + xv[0]xv[0] = xv[1]; \\ update xv[1] = *input; \\ update yv[0] = yv[1];\\update yv[1] = *output; \\update }

Now the loop may be incorporated around the allpass filter as per theequations above. This is trivially realized by the following:

void bell(float *xv, float *yv, float gain, float *input, float *output){ allpass(xv, yv, input, output); *output = 0.5 * (1.0−gain) *(*output) + 0.5 * (1.0+gain) * (*input); }

More concisely, the previous two code snippets can be combined into asingle routine that looks like this:

void bell(float *xv, float *yv, float gain, float *input, float *output){ float ap_output = geq_b0 * (*input − yv[0]) + geq_b1 * (xv[1] −yv[1]) + xv[0] xv[0] = xv[1]; \\ update xv[1] = *input; \\ update yv[0]= yv[1]; \\update yv[1] = *output; \\update *output = 0.5 * (1.0−gain) *ap_output + 0.5 * (1.0+gain) * (*input); }

The first-order filter will now be examined in detail. These filters canbe described by the transfer function

${H(z)} = \frac{b_{0} + {b_{1}z^{- 1}}}{1 + {a_{1}z^{- 1}}}$

which corresponds to the difference equation

y[k]=b ₀ x[k]+b ₁ x[k−1]−a ₁ y[k−1].

FIG. 12 illustrates the DF1 architecture for a first-order filteraccording to one embodiment of the present invention. Referring now toFIG. 12, the multiplier coefficients in this filter structure correspondin a clear way to the coefficients in the transfer function and in thedifference equation. The output of the digital filter is computed asfollows:

Initially, every one of the state variables is set to zero. In otherwords,

x[−1]=y[−1]=0.

At time k=0 the following computation is done, according to FIG. 11:

y[0]=b ₀ x[0]+b ₁ x[−1]−a ₁ y[−1].

Then, the registers are then updated so that the register marked byx[k−1] now holds x[0], and the register marked by y[k−1] holds y[0].

At time k=1 the following computation is done:

y[1]=b ₀ x[1]+b ₁ x[0]−a ₁ y[0].

Then, the register update is again completed so that the register markedby x[k−1] now holds x[1] and the register marked by y[k−1] holds y[1].

This process is then repeated over and over for all instants k: A newinput, x[k], is brought in, a new output y[k] is computed, and the statevariables are updated.

In general, then, the digital filtering operation can be viewed as a setof multiplications and additions performed on a data stream x[0], x[1],x[2], . . . using the coefficients b0, b1, a1 and the state variablesx[k−1], y[k−1].

FIG. 13 is a block diagram illustrating an example digital signalprocessing system 1300 in accordance with the systems and methodsdescribed herein. Referring now to FIG. 13, the example digital signalprocessing system 1300 may process wireless input signals 1302 that areinput into a wireless receiver 1304. The wireless signals 1302 may beamplitude modulation signals, frequency modulation signals, digitallymodulated signals, or other types of transmitted signals. The wirelessreceiver 1304 may be configured to receive the type of wireless inputsignal used, e.g., digitally modulated signals, etc.

In various embodiments, the wireless receiver 1304 may receive thewireless input signal 1302 and conditions it prior to processing by adigital processing device such as the digital signal processor(DSP)1306. For example, in some embodiments, high-level amplifiedsignals may be conditioned to reduce the signal's range so that they arenot outside the dynamic range of the analog-to-digital converters. Theconditioned signal may then be input into a DSP 1306.

The DSP block 1306 may include necessary components for processing theinput signals as described herein. For example, the DSP 1306 may runvarious digital processing algorithms, including, for example, noisecancellation algorithms other algorithms described herein. Thesealgorithms may process audio signals to produce studio-quality sound.

The DSP 1306 may be coupled to an amplifier 1308 that amplifies theprocessed audio signal and provides an output signal for the headphonedrivers 1310. In some embodiments, the amplifier 1308 may include amulti-channel amplification section, such as a stereo amplifier. In someexamples, multiple stereo amplifiers may be used.

In the amplifier 1308, the level of the output signal may be raised sothat it may be reproduced using the headphone driver 1310 to drive audiotransducers, e.g., a pair of headphones. The audio transducer may beused to provide sound to a listener.

Headphones may include earphones, earbuds, stereophones, and headsets.The headphones generally comprise a pair of small loudspeakers, or, insome embodiments, a single speaker. The small loudspeaker orloudspeakers may be formed such that a user can hold them close to orwithin a user's ears. The headphones can include a connection device,such as a connector to connect the headphones to, e.g., an audio signalsource such as the headphone driver 1310. In some cases, the headphonesused may be wireless headphones. In such an embodiment, a separatetransmitter (not shown) can be connected to headphone drivers 1310. Thistransmitter can then transmit a signal to the wireless headphone. Thiscan allow a person wearing the headphones to move about more freelywithout having to be concerned for wires, which may get in the way orlimit movement. Additionally, some embodiments may include noisecancellation headphones.

In other embodiments, a connector, e.g., a headphone connector might beused in conjunction with other, circuitry to drive other types of audiotransducers, such as speakers include full range drivers, subwoofers,woofers, mid-range drivers, and tweeters. These speakers might be hornloudspeakers, piezoelectric speakers, electrostatic loudspeakers, ribbonand planar magnetic loudspeakers, bending wave loudspeakers, flat panelloudspeakers, distributed mode loudspeakers, heil air motiontransducers, or plasma arc speakers, to name a few. The speakers may beincluded in speaker enclosures, headphones, etc. In certain embodiments,a power supply 1312 may provide power to the circuit DSP 1306,amplifier, as well as other circuit elements, such as the system clocks1314, mater control unit 1316, and the wireless receiver 1304. In someembodiments, the power supply includes a battery that may store andprovide power. The power from this battery, or other power source, suchas a home alternating current power source, can be conditioned in thepower supply 1312. In embodiments that use a battery to provide power,the power supply 1312 may also include various circuitry to charge thebattery.

The systems clocks 1314 generate and provide timing signals, e.g., clocksignals to control the timing in the device 1300. A crystal or otheroscillator may be used to generate the system clocks 1304. In someexamples, a master clock may be divided to generate the needed clocksignals.

The systems and methods described herein may include a power supplycircuit 1312. The power supply circuitry 1312 takes supplied voltage,converts and conditions it and provides power for various circuits usedto process the audio signals.

A master control unit (MCU) 1316 can be used to control the overallfunctionality of the device 1300. For example, in some embodiments, theMCU 1316 may boot, run, and control other circuits in the device 1300.

In some embodiments, the systems and methods described herein may beused in a device external to a personal listening device, such as a setof headphones. In this way, the external device may drive the headphonesand allow a listener to listen to, e.g., music. In other embodiments,the systems and methods described herein may be incorporated into a setof headphones. These systems and methods may be incorporated into, e.g.,a set of headphones via a DSP in the headphone circuitry. This may allowa manufacturer or user in the context where the systems and methods areused in vehicles (e.g., Ford, GM, Toyota, Hyundai etc) the ability tocreate a custom profile or ‘sound’ for their specific vehicles and/orbrands or types of vehicles (cars, trucks, SUVs, buses, RV's, militaryvehicles, such as tanks) and/or product lines. For example, in somecases a user might own multiple vehicles and might want each vehicle toprovide a similar sound experience when using headphones in each of thevehicles. Alternatively, a user might want the sound experience whileusing the headphones to be the same or similar to a sound experience ina particular car when headphones are not used, e.g., when a head unitand speakers are used with the systems and methods described herein toproduce, for example, studio quality sound. Accordingly, in someembodiments, the systems and methods described herein might be used tocreate the same or similar sound experience across multiple vehicles,using either headphones or speakers.

In some examples, the manufacturer or user can create profiles to suitthe tastes of their customer and the vehicles they use or purchase. Inother embodiments, the users of the headphones or other personallistening device may create there own profile by, for example, using apair of headphones incorporating these systems and methods to listen tomusic and adjusting the system based on, for example, personalpreferences. For example, when a user listens to music using theheadphones or other personal listening device, they might adjust theprocessing of the music by adjusting a first low shelf filter, a firstcompressor, or a graphic equalizer. They might also change theprocessing of the music signal by adjusting a second compressor andadjust the gain of the compressed signal after the second compressor. Insome examples, the user may adjust an amplifier that increases theamplitude of the signal into an input of headphone drivers.

Various embodiments of these systems and methods may be used inconjunction with vehicles in addition to cars, such as pickup trucks,SUV's, trucks, tractors, buses, etc. In some examples, these systems andmethods may also be used in conjunction with aviation and manneapplications. In various embodiments, these systems and methods may alsobe used in other areas were, e.g., headphones might be used to listen tomusic, for example, homes, offices, trailers, etc.

Referring back to the equations above, a first-order shelving filter canbe created by applying the equation

${A(z)} = \frac{k_{2} + {{k_{1}( {1 + k_{2}} )}z^{- 1}} + z^{- 2}}{1 + {{k_{1}( {1 + k_{2}} )}z^{- 1}} + {k_{2}z^{- 2}}}$

to the first-order allpass filter A(z), where

${A(z)} = \frac{\alpha - z^{- 1}}{1 - {\alpha \; z^{- 1}}}$

where α is chosen such that

$\alpha = \frac{( {1 - {\sin ( \frac{2\pi \; f_{c}}{F_{s}} )}} )}{\cos ( \frac{2\pi \; f_{c}}{F_{s}} )}$

where fc is the desired corner frequency and Fs is the samplingfrequency. The allpass filter A(z) above corresponds to the differenceequation

y[k]=αx[k]−x[k−1]+αy[k−1].

If allpass coefficient α is referred to as allpass coef and the equationterms are rearranged, the above equation becomes

y[k]=allpass_coef(x[k]+y[k−1]−x[k−1].

This difference equation corresponds to a code implementation of ashelving filter that is detailed below.

One specific software implementation of digital signal processing method100 will now be detailed.

Input gain adjustment 101 and output gain adjustment 109, describedabove, may both be accomplished by utilizing a “scale” function,implemented as follows:

void scale(gain, float *input, float *output) { for (i = 0; i <NSAMPLES; i++) { *output++ = inputGain * (*input++);} }

First low shelf filter 102 and second low shelf filter 105, describedabove, may both be accomplished by utilizing a “low shelf” function,implemented as follows:

void low_shelf(float *xv, float *yv, float *wpt, float *input, float*output) { float l; int i; for (i = 0; i < NSAMPLES; i++) { if (wpt[2] <0.0) \\ cut mode, use conventional realization { \\ allpass_coef = alphayv[0] = ap_coef * (*input) + (ap_coef * ap_coef − 1.0) * xv[0]; xv[0] =ap_coef * xv[0] + *input; *output++ = 0.5 * ((1.0 + wpt[0]) *(*input++) + (1.0 − wpt[0]) * yv[0]); } else \\ boost mode, use specialrealization { 1 = (ap_coef * ap_coef − 1.0) * xv[0]; *output = wpt[1] *((*input++) − 0.5 * (1.0 − wpt[0]) * 1);  xv[0] = ap_coef * xv[0] +*output++; } } }

As this function is somewhat complicated, a detailed explanation of itis proper. First, the function declaration provides:

-   -   void low_shelf(float*xv, float*yv, float*wpt,        float*input,float*output)

The “low_shelf” function takes as parameters pointers to five differentfloating-point arrays. The arrays xv and yv contain the “x” and “y”state variables for the filter. Because the shelving filters are allfirst-order filters, the state-variable arrays are only of length one.There are distinct “x” and “y” state variables for each shelving filterused in digital signal processing method 100. The next array used is thearray of filter coefficients “wpt” that pertain to the particularshelving filter. wpt is of length three, where the elements wpt[0],wpt[1], and wpt[2] describe the following:

wpt[0]=G

wpt[1]=2[(1+G)+α(1−G)]⁻¹

wpt[2]=−1 when cutting,1 when boosting

and α is the allpass coefficient and G is the shelving filter gain. Thevalue of α is the same for all shelving filters because it is determinedsolely by the corner frequency (it should be noted that and all four ofthe shelving filters in digital signal processing method 100 have acorner frequency of 1 kHz). The value of G is different for each of thefour shelving filters.

The array “input” is a block of input samples that are fed as input toeach shelving filter, and the results of the filtering operation arestored in the “output” array.

The next two lines of code,

Float 1;

int i;

allocate space for a loop counter variable, i, and an auxiliaryquantity, 1, which is the quantity 10[k] from FIG. 9.

The next line of code,

for (i=0; i<NSAMPLES; i++)

performs the code that follows a total of NSAMPLES times, where NSAMPLESis the length of the block of data used in digital signal processingmethod 100.

This is followed by the conditional test

if (wpt[2]<0,0)

and, recalling the equations discussed above, wpt[2]<0 corresponds to ashelving filter that is in “cut” mode, whereas wpt[2]>=0 corresponds toa shelving filter that is in “boost” mode. If the shelving filter is incut mode the following code is performed:

if (wpt[2] < 0.0) \ \ cut mode, use conventional realization { \ \allpass_coef = alpha yv[0] = ap_coef * (*input) + (ap_coef * ap_coef −1.0) * xv[0]; xv[0] = ap_coef * xv[0] + *input; *output++ = 0.5 *((1.0 + wpt[0]) * (*input++) + (1.0 − wpt[0]) * yv[0]); }

The value xv[0] is simply the state variable x[k] and yv[0] is justyv[k]. The code above is merely an implementation of the equations

y[k] = α ⋅ in[k] + (α² − 1) ⋅ x[k] x[k] = α ⋅ x[k] + in[k]${{out}\lbrack k\rbrack} = {\frac{1}{2}( {{( {1 + G} ) \cdot {{in}\lbrack k\rbrack}} + {( {1 - G} ) \cdot {y\lbrack k\rbrack}}} )}$

If the shelving filter is in cut mode the following code is performed:

else \\ boost mode, use special realization { 1 = (ap_coef * ap_coef −1.0) * xv[0]; *output = wpt[1] * ((*input++) − 0.5 * (1.0 − wpt[0]) *1); xv[0] = ap_coef * xv[0] + *output++; }

which implements the equations

i₀[k] = (α² − 1) ⋅ x[k]${{out}\lbrack k\rbrack} = {{{2\lbrack {( {1 + G} ) + {\alpha ( {1 - G} )}} \rbrack}^{- 1} \cdot {{in}\lbrack k\rbrack}} - {\frac{1}{2}( {1 - G} ){i_{0}\lbrack k\rbrack}}}$x[k] = α ⋅ x[k − 1] + out[k]

First high shelf filter 103 and second high shelf filter 106, describedabove, may both be accomplished by utilizing a “high_shelf” function,implemented as follows:

void high_shelf(float *xv, float *yv, float *wpt, float *input, float*output) { float l; int i; for (i = 0; i < NSAMPLES; i++) { if (wpt[2] <0.0) \\ cut mode, use conventional realization, { \\ allpass_coef =alpha yv[0] = allpass_coef * (*input) + (allpass_coef * allpass_coef −1.0) * xv[0]; xv[0] = allpass_coef * xv[0] + *input; *output++ = 0.5 *((1.0 + wpt[0]) * (*input++) − (1.0 − wpt[0]) * yv[0]); } else \\ boostmode, use special realization { l = (allpass_coef * allpass_coef −1.0) * xv[0]; *output = wpt[1] * ((*input++) + 0.5 * (1.0 − wpt[0]) *l); xv[0] = allpass_coef * xv[0] + *output++; } } }

Implementing the high-shelving filter is similar to implementing thelow-shelving filter. Comparing the two functions above, the onlysubstantive difference is in the sign of a single coefficient.Therefore, the program flow is identical.

Graphic equalizer 107, described above, may be implemented using aseries of eleven calls to a “bell” filter function, implemented asfollows:

void bell(float *xv, float *yv, float *wpt, float *input, float *output){ float geq_gain = wpt[0]; \\ G float geq_b0 = wpt[1]; \\ k2 floatgeq_b1 = wpt[2]; \\ k1(1+k2) float ap_output; int i; for (i = 0; i <NSAMPLES; i++) { ap_output = geq_b0 * (*input − yv[0]) + geq_b1 * (xv[1]− yv[1]) + xv[0]; xv[0] = xv[1]; \\ update xv[1] = *input; \\ updateyv[0] = yv[1]; \\update yv[1] = *output; \\update *output++ = 0.5 *(1.0−gain) * ap_output + 0.5 * (1.0+gain) * (*input++): } }

The function bell( ) takes as arguments pointers to arrays xv (the “x”state variables), yv (the “y” state variables), wpt (which contains thethree graphic EQ parameters G, k2, and k1(1+k2)), a block of inputsamples “input”, and a place to store the output samples. The first fourstatements in the above code snippet are simple assignment statementsand need no explanation.

The for loop is executed NSAMPLES times, where NSAMPLES is the size ofthe block of input data. The next statement does the following:

ap _(output) =geq _(b0)*(*input−yv[0])+geq _(b1)*(xv[1]−yv[1])+xv[0]

The above statement computes the output of the allpass filter asdescribed above. The next four statements do the following:

xv[0]=xv[1];

shifts the value stored in x[k−1] to x[k−2].

xv[1]=*input;

shifts the value of input[k] to x[k−1].

yv[0]=yv[1];

shifts the value stored in y[k−1] to y[k−2].

yv[1]=*output;

shifts the value of output[k], the output of the allpass filter, toy[k−1].

Finally, the output of the bell filter is computed as

*output++=0.5*(1.0−gain)*ap_output+0.5*(1.0+gain)*(*input++);

First compressor 104 and second compressor 108, described above, may beimplemented using a “compressor” function, implemented as follows:

void compressor(float *input, float *output, float *wpt, int index) {static float level; float interp, GR, excessGain, L, invT, ftempabs;invT = wpt[2]; int i, j; for (i = 0; i < NSAMPLES; i ++) { ftempabs =fabs(*input++); level = (ftempabs >= level)? wpt[0] * (level −ftempabs) + ftempabs : wpt[1] * (level − ftempabs) + ftempabs; GR = 1.0;if (level * invT > 1.0) { excessGain = level *invT; interp = excessGain− trunc(excessGain); j = (int) trunc(excessGain) − 1; if (j < 99) { GR =table[index][j] + interp * (table[index][j+1] − table[index][j]); //table[ ][ ] is the exponentiation table } else { GR = table[index][99];} } *output++ = *input++ * GR; } }

The compressor function takes as input arguments pointers to input,output, and wpt arrays and an integer, index. The input and outputarrays are used for the blocks of input and output data, respectively.The first line of code,

static float level;

allocates static storage for a value called “level” which maintains thecomputed signal level between calls to the function. This is because thelevel is something that needs to be tracked continuously, for the entireduration of the program, not just during execution of a single block ofdata.

The next line of code,

float interp, GR, excessGain, L, invT, ftempabs;

allocates temporary storage for a few quantities that are used duringthe computation of the compressor algorithm; these quantities are onlyneeded on a per-block basis and can be discarded after each pass throughthe function.

The next line of code,

invT=wpt[2];

extracts the inverse of the compressor threshold, which is stored inwpt[2], which is the third element of the wpt array. The other elementsof the wpt array include the attack time, the release time, and thecompressor ratio.

The next line of code indicates that the compressor loop is repeatedNSAMPLES times. The next two lines of code implement the levelcomputation as per

level=(ftempabs>=level)?wpt[0]*(level·about·ftempabs)+ftempbas:wpt[1]−*(level−ftempabs)+ftempabs;

is equivalent to the expanded statement

if (ftempabs >= level) { level = wpt[0] * (level − ftempabs) + ftempabs;} else { level = wpt[1] * (level − ftempabs) + ftempabs;

which is what is needed to carry out the above necessary equation, withwpt[0] storing the attack constant α_(att) and wpt[1] storing therelease constant α_(rel).

Next, it can be assumed that the gain reduction, GR, is equal to unity.Then the comparison

if(level*invT>1.0)

is performed, which is the same thing as asking if level >T, i.e., thesignal level is over the threshold. If it is not, nothing is done. If itis, the gain reduction is computed. First, the excess gain is computedas

excessGain=level*invT;

as calculated using the equations above. The next two statements,

interp=excessGain−trunc(excessGain);

j=(int)trunc(excessGain)−1;

compute the value of index into the table of exponentiated values, asper the equations above. The next lines,

if (j < 99) { GR = table[index][j] + interp * (table[index][j+i] −table[index][j]); // table[ ][ ] is the exponentiation table } else { GR= table[index][99]; }

implement the interpolation explained above. The two-dimensional array,“table,” is parameterized by two indices: index and j. The value j issimply the nearest integer value of the excess gain. The table hasvalues equal to

${{{table}\lbrack{index}\rbrack}\lbrack j\rbrack} = {(j)\frac{1 - {index}}{index}}$

which can be recognized as the necessary value from the equations above,where the “floor” operation isn't needed because j is an integer value.Finally, the input is scaled by the computed gain reduction, GR, as per

*output++=*input++*GR;

and the value is written to the next position in the output array, andthe process continues with the next value in the input array until allNSAMPLE values in the input block are exhausted.

It should be noted that in practice, each function described above isgoing to be dealing with arrays of input and output data rather than asingle sample at a time. This does not change the program much, ashinted by the fact that the routines above were passed their inputs andoutputs by reference. Assuming that the algorithm is handed a block ofNSAMPLES in length, the only modification needed to incorporate arraysof data into the bell-filter functions is to incorporate looping intothe code as follows:

void bell(float *xv, float *yv, float gain, float *input, float *output){ float ap_output; int i; for (i = 0; i < NSAMPLES; i++) { ap_output =geq_b0 * (*input − yv[0]) + geq_b1 * (xv[1] − yv[1]) + xv[0] xv[0] =xv[1]; \\ update xv[1] = *input; \\ update yv[0] = yv[1]; \\update yv[1]= *output; \\update *output++ = 0.5 * (1.0−gain) * ap_output + 0.5 *(1.0+gain) * (*input++); } }

Digital signal processing method 100 as a whole, may be implemented as aprogram that calls each of the above functions, implemented as follows:

// it is assumed that floatBuffer contains a block of // NSAMPLESsamples of floating-point data. // The following code shows theinstructions that // are executed during a single pass scale(inputGain,floatBuffer, floatBuffer); low_shelf(xv1_ap, yv1_ap, &working_table[0],floatBuffer, floatBuffer); high_shelf(xv2_ap, yv2_ap, &working_table[3],floatBuffer, floatBuffer); compressor(floatBuffer, floatBuffer,&working_table[6], ratio1Index); low_shelf(xv3_ap_left, yv3_ap_left,xv3_ap_right, yv3_ap_right, &working_table[11], floatBuffer,floatBuffer); high_shelf(xv4_ap_left, yv4_ap_left, xv4_ap_right,yv4_ap_right, &working_table[14], floatBuffer, floatBuffer);bell(xv1_geq, yv1_geq, &working_table[17], floatBuffer, floatBuffer);bell(xv2_geq, yv2_geq, &working_table[20], floatBuffer, floatBuffer);bell(xv3_geq, yv3_geq, &working_table[23], floatBuffer, floatBuffer);bell(xv4_geq, yv4_geq, &working_table[26], floatBuffer, floatBuffer);bell(xv5_geq, yv5_geq, &working_table[29], floatBuffer, floatBuffer);bell(xv6_geq, yv6_geq, &working_table[32], floatBuffer, floatBuffer);bell(xv7_geq, yv7_geq, &working_table[35], floatBuffer, floatBuffer);bell(xv8_geq, yv8_geq, &working_table[38], floatBuffer, floatBuffer);bell(xv9_geq, yv9_geq, &working_table[41], floatBuffer, floatBuffer);bell(xv10_geq, yv10_geq, &working_table[44], floatBuffer, floatBuffer);bell(xv11_geq, yv11_geq, &working_table[47], floatBuffer, floatBuffer):compressor(floatBuffer, floatBuffer, &working_table[50], ratio1Index);scale(outputGain, floatBuffer, floatBuffer);

As can be seen, there are multiple calls to the scale function, the lowshelf function, the high shelf function, the bell function, and thecompressor function. Further, there are references to arrays called xv1,yv1, xv2, yv2, etc. These arrays are state variables that need to bemaintained between calls to the various routines and they store theinternal states of the various filters in the process. There is alsorepeated reference to an array called working_table. This table holdsthe various pre-computed coefficients that are used throughout thealgorithm. Algorithms such as this embodiment of digital signalprocessing method 100 can be subdivided into two parts: the computationof the coefficients that are used in the real-time processing loop andthe real-time processing loop itself. The real-time loop consists ofsimple multiplications and additions, which are simple to perform inreal-time, and the coefficient computation, which requires complicatedtranscendental functions, trigonometric functions, and other operations,which cannot be performed effectively in real-time. Fortunately, thecoefficients are static during run-time and can be pre-computed beforereal-time processing takes place. These coefficients can be specificallycomputed for each audio device in which digital signal processing method100 is to be used. Specifically, when digital signal processing method100 is used in a mobile audio device configured for use in vehicles,these coefficients may be computed separately for each vehicle the audiodevice may be used in to obtain optimum performance and to account forunique acoustic properties in each vehicle such as speaker placement,passenger compartment design, and background noise.

For example, a particular listening environment may produce suchanomalous audio responses such as those from standing waves. Forexample, such standing waves often occur in small listening environmentssuch as an automobile. The length of an automobile, for example, isaround 400 cycles long. In such an environment, some standing waves areset up at this frequency and some below. Standing waves present anamplified signal at their frequency, which may present an annoyingacoustic signal. Vehicles of the same size, shape, and of the samecharacteristics, such as cars of the same model, may present the sameanomalies due to their similar size, shape, structural make-up, speakerplacement, speaker quality, and speaker size. The frequency and amountof adjustment performed, in a further embodiment, may be configured inadvance and stored for use in graphic equalizer 107 to reduce anomalousresponses for future presentation in the listening environment.

The “working tables” shown in the previous section all consist ofpre-computed values that are stored in memory and retrieved as needed.This saves a tremendous amount of computation at run-time and allowsdigital signal processing method 100 to run on low-cost digital signalprocessing chips.

It should be noted that the algorithm as detailed in this section iswritten in block form. The program described above is simply a specificsoftware embodiment of digital signal processing method 100, and is notintended to limit the present invention in any way. This softwareembodiment may be programmed upon a computer chip for use in an audiodevice such as, without limitation, a radio, MP3 player, game station,cell phone, television, computer, or public address system. Thissoftware embodiment has the effect of taking an audio signal as input,and outputting that audio signal in a modified form.

While various embodiments of the present invention have been describedabove, it should be understood that they have been presented by way ofexample only, and not of limitation. Likewise, the various diagrams maydepict an example architectural or other configuration for theinvention, which is done to aid in understanding the features andfunctionality that can be included in the invention. The invention isnot restricted to the illustrated example architectures orconfigurations, but the desired features can be implemented using avariety of alternative architectures and configurations. Indeed, it willbe apparent to one of skill in the art how alternative functional,logical, or physical partitioning and configurations can be implementedto implement the desired features of the present invention. In addition,a multitude of different constituent module names other than thosedepicted herein can be applied to the various partitions. Additionally,with regard to flow diagrams, operational descriptions and methodclaims, the order in which the steps are presented herein shall notmandate that various embodiments be implemented to perform the recitedfunctionality in the same order unless the context dictates otherwise.

Terms and phrases used in this document, and variations thereof, unlessotherwise expressly stated, should be construed as open ended as opposedto limiting. As examples of the foregoing: the term “including” shouldbe read as meaning “including, without limitation” or the like; the term“example” is used to provide exemplary instances of the item indiscussion, not an exhaustive or limiting list thereof; the terms “a” or“an” should be read as meaning “at least one,” “one or more” or thelike; and adjectives such as “conventional,” “traditional,” “normal,”“standard,” “known” and terms of similar meaning should not be construedas limiting the item described to a given time period or to an itemavailable as of a given time, but instead should be read to encompassconventional, traditional, normal, or standard technologies that may beavailable or known now or at any time in the future. Likewise, wherethis document refers to technologies that would be apparent or known toone of ordinary skill in the art, such technologies encompass thoseapparent or known to the skilled artisan now or at any time in thefuture.

The presence of broadening words and phrases such as “one or more,” “atleast,” “but not limited to” or other like phrases in some instancesshall not be read to mean that the narrower case is intended or requiredin instances where such broadening phrases may be absent. The use of theterm “module” does not imply that the components or functionalitydescribed or claimed as part of the module are all configured in acommon package. Indeed, any or all of the various components of amodule, whether control logic or other components, can be combined in asingle package or separately maintained and can further be distributedin multiple groupings or packages or across multiple locations.

Additionally, the various embodiments set forth herein are described interms of exemplary block diagrams, flow charts and other illustrations.As will become apparent to one of ordinary skill in the art afterreading this document, the illustrated embodiments and their variousalternatives can be implemented without confinement to the illustratedexamples. For example, block diagrams and their accompanying descriptionshould not be construed as mandating a particular architecture orconfiguration.

Now that the invention has been described,

What is claimed is:
 1. A method for processing a digital signalcomprising: adjusting a gain of the digital signal a first time, using adigital processing device; processing the adjusted signal with a firstlow shelf filter and a first high shelf filter, using the digitalprocessing device, compressing the filtered signal with a firstcompressor, using the digital processing device; processing the signalwith a second low she filter and a second high shelf filter, using thedigital processing device, processing the signal with a graphicequalizer, using the digital processing device; compressing theprocessed signal with a second compressor, using the digital processingdevice; adjusting the gain of the compressed signal a second time, usingthe digital processing device; outputting the signal, from the digitalprocessing device through an amplifier and driver circuit in a personalaudio listening device.
 2. The method of claim 1, wherein the personalaudio listening device is a pair of headphones.
 3. The method of claim2, wherein the personal audio listening device is used within a vehicle.4. The method of claim 3, further comprising creating a sound profilefor a vehicle where the personal audio listening device will be used. 5.The method of claim 1, wherein the audio signal is received wirelessly.6. The method of claim 1, wherein the digital signal represents an audiosignal.
 7. The method of claim 1, wherein adjusting the gain of thereceived signal a first time is done with a first gain amplifier andadjusting the gain of the signal a second time is done with a secondgain amplifier.
 8. The method of claim 1, wherein the first low shelffilter has a cutoff frequency at 1000 Hz.
 9. The method of claim 1,wherein the first high shelf filter has a cutoff frequency at 1000 Hz.10. The method of claim 1, wherein the graphic equalizer compriseseleven cascading second order filters.
 11. The method of claim 10,wherein each of the second order filters is a bell filter.
 12. Themethod of claim 11, wherein the first of the eleven filters has a centerfrequency of 30 Hz and the eleventh filter of the eleven filters has acenter frequency of 16000 Hz.
 13. The method of claim 12, wherein thesecond to tenth filters are centered at approximately one octaveintervals from each other.
 14. The audio system of claim 1, wherein thesecond low shelf filter is a magnitude-complementary low-shelf filter.15. The audio system of claim 1, further comprising a set of headphonescoupled to the driver circuit.
 16. An audio system comprising: apersonal audio listening device; a digital processing device coupled tothe personal audio listening device, the digital processor deviceincluding: a first gain amplifier configured to amplify a signal; afirst low shelf filter and a first high shelf filter configured toprocess the amplified signal; a first compressor configured to compressthe filtered signal; a second low she filter and a second high shelffilter configured to process the first compressed signal; a secondcompressor configured to compress the processed signal; and a secondgain amplifier configured to amplify the gain of the second compressedsignal and to output an output signal; and a personal audio listeningdevice driver coupled to an output of the digital processing device andconfigured to drive the personal audio listening device such that itemits sound.
 17. The audio system of claim 16, wherein the personalaudio listening device is a pair of headphones.
 18. The audio system ofclaim 17, wherein the personal audio listening device is used within avehicle.
 19. The audio system of claim 18, further comprising creating asound profile for a vehicle where the personal audio listening devicewill be used.
 20. The audio system at claim 16, wherein the signal is anaudio signal.
 21. The speaker system of claim 16, wherein the first lowshelf filter has a cutoff frequency at 1000 Hz.
 22. The audio system ofclaim 16, wherein the first high shelf filter has a cutoff frequency at1000 Hz.
 23. The audio system of claim 16, wherein the graphic compriseseleven cascading second order filters.
 24. The audio system of claim 23,wherein each of the second order filter is a bell filter.
 25. The audiosystem of claim 24, wherein the first of the eleven filters has a centerfrequency of 30 Hz, and the eleventh filter of the eleven filters has acenter frequency of 16000 Hz.
 26. The audio system of claim 25, whereinthe second to tenth filters are centered at approximately one octaveintervals from each other.
 27. The audio system of claim 16, wherein thesecond low she if filter is a magnitude-complementary low-shelf filter.28. The audio system of claim 16, further comprising profile concretioncircuitry configured to allow a user to create a sound profile for anarea by listening to music in the area and adjusting the audio system.29. The audio system of claim 16, further comprising a wireless receiverconfigured to receive audio signals wirelessly from a transmitter.
 30. Amethod for processing an audio signal comprising: receiving an audiosignal; adjusting a gain of the audio signal a first time using aseparate digital processing device located between a radio head unit anda speaker; processing the audio signal with a first low shelf filterusing the digital processing device; processing the audio signal with afirst high shelf filter using the digital processing device; processingthe audio signal with a first compressor using the digital processingdevice; processing the audio signal with a second low shelf filter usingthe digital processing device; processing the audio signal with a secondhigh shelf filter using the digital processing device; processing theaudio signal with a graphic equalizer using the digital processingdevice; processing the audio signal with a second compressor using thedigital processing device; adjusting the gain of the audio signal asecond time using the digital processing device; and outputting theaudio signal from the digital processing device to a personal audiolistening device driver.
 31. The method of claim 30, wherein thepersonal audio listening device is a pair of headphones.
 32. The methodof claim 31, wherein the personal audio listening device is used withina vehicle.
 33. The method of claim 32, further comprising creating asound profile for a vehicle where the personal audio listening devicewill be used.
 34. The method of claim 30, wherein the first low shelffilter has a cutoff frequency at 1000 Hz.
 35. The method of claim 30,wherein the first high shelf filter has a cutoff frequency at 1000 Hz.36. The method of claim 30, wherein the graphic equalizer compriseseleven cascading second order bell filters.
 37. The method of claim 30,further comprising connecting the driver to a set of headphones.
 38. Themethod of claim 30, further comprising determining a profile for avehicle where the headphones will be used.
 39. The method of claim 30,further comprising receiving the audio signal wirelessly.